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AP Association for Proportional Fairness in Multirate WLANs

机译:AP多速率WLAN比例公平协会

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摘要

In this paper, we investigate the problem of achieving proportional fairness via access point (AP) association in multirate WLANs. This problem is formulated as a nonlinear programming with an objective function of maximizing the total user bandwidth utilities in the whole network. Such a formulation jointly considers fairness and AP selection. We first propose a centralized algorithm Non-Linear Approximation Optimization for Proportional Fairness (NLAO-PF) to derive the user–AP association via relaxation. Since the relaxation may cause a large integrality gap, a compensation function is introduced to ensure that our algorithm can achieve at least half of the optimal in the worst case. This algorithm is assumed to be adopted periodically for resource management. To handle the case of dynamic user membership, we propose a distributed heuristic Best Performance First (BPF) based on a novel performance revenue function, which provides an AP selection criterion for newcomers. When an existing user leaves the network, the transmission times of other users associated with the same AP can be redistributed easily based on NLAO-PF. Extensive simulation study has been performed to validate our design and to compare the performance of our algorithms to those of the state of the art.
机译:在本文中,我们研究了在多速率WLAN中通过访问点(AP)关联实现比例公平的问题。这个问题被表述为一个非线性规划,其目标功能是使整个网络中的总用户带宽效用最大化。这样的表述考虑了公平性和接入点选择。我们首先提出一种用于比例公平的集中算法非线性近似优化(NLAO-PF),以通过松弛导出用户-AP关联。由于松弛可能会导致较大的整体性差距,因此引入了补偿函数以确保我们的算法在最坏的情况下至少可以达到最优值的一半。假定此算法定期用于资源管理。为了处理动态用户成员身份的情况,我们提出了一种基于新型性能收益函数的分布式启发式最佳性能优先(BPF),该功能为新用户提供AP选择标准。当现有用户离开网络时,可以基于NLAO-PF轻松重新分配与同一AP关联的其他用户的传输时间。已经进行了广泛的仿真研究,以验证我们的设计,并将我们的算法的性能与现有技术进行比较。

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